vignettes/articles/accessing_project_data.Rmd
accessing_project_data.RmdThis article walks through, in detail, accessing data specific to
projects, primarily via mermaid_get_project_data().
To access data related to your MERMAID projects, first obtain a list
of your projects with mermaid_get_my_projects().
At this point, you will have to authenticate to the Collect app. R will help you do this automatically by opening a browser window for you to log in to Collect, either via Google sign-in or username and password - however you normally do!
Once you’ve logged in, come back to R. Your login credentials will be stored for a day, until they expire, and you will need to login again. The package handles the expiration for you, so just log in again when prompted.
library(mermaidr)
my_projects <- mermaid_get_my_projects()
my_projects
#> # A tibble: 19 × 15
#> id name countries num_sites tags notes status data_policy_beltfish
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 02e6915c-1c64-4d2c-bac0-32… TWP … Indonesia 14 "WCS… "" Open Private
#> 2 170e7182-700a-4814-8f1e-45… 2018… Fiji 10 "WCS… "Thi… Open Private
#> 3 173c2353-3ee3-49d1-b08a-a6… Copy… Fiji 8 "WCS… "Nam… Open Public Summary
#> 4 1fbdb9ea-9adf-4038-bbe2-52… a2 Canada, … 9 "WWF… "Nam… Open Private
#> 5 2c0c9857-b11c-4b82-b7ef-e9… Shar… Canada, … 27 "" "dhf… Open Public Summary
#> 6 2d6cee25-c0ff-4f6f-a8cd-66… WCS … Mozambiq… 74 "WCS… "Dat… Open Private
#> 7 3a9ecb7c-f908-4262-8769-1b… Aceh… Indonesia 18 "WCS… "" Open Private
#> 8 4080679f-1145-4d13-8afb-c2… Mada… Madagasc… 74 "WCS… "MAC… Open Private
#> 9 4d23d2a1-774f-4ccf-b567-69… Mada… Madagasc… 16 "WCS… "Mon… Open Public Summary
#> 10 507d1af9-edbd-417e-a65c-35… Kari… Indonesia 43 "WCS… "" Open Private
#> 11 5679ef3d-bafc-453d-9e1a-a4… Mada… Madagasc… 33 "WCS… "" Open Public Summary
#> 12 5f13e6dc-40cc-4ef9-9c16-ae… Copy… Indonesia 43 "WCS… "" Open Public Summary
#> 13 75ef7a5a-c770-4ca6-b9f8-83… Kubu… Fiji 78 "WCS… "" Open Private
#> 14 7a6bfd69-6635-4281-937c-2b… Copy… Belize 31 "WCS… "" Open Public Summary
#> 15 9de82789-c38e-462e-a1a8-e0… XPDC… Indonesia 37 "" "XPD… Open Private
#> 16 a1b7ff1f-81cd-4efc-978b-cf… Grea… Fiji 76 "Uni… "" Open Private
#> 17 bacd3529-e0f4-40f4-a089-99… Beli… Belize, … 32 "WCS… "" Open Public Summary
#> 18 d065cba4-ed09-47fd-89fb-22… 2019… Fiji 31 "WCS… "Ble… Open Private
#> 19 e1efb1e0-0af8-495a-9c69-fd… 2016… Fiji 8 "WCS… "Nam… Open Private
#> # ℹ 7 more variables: data_policy_benthiclit <chr>, data_policy_benthicpit <chr>,
#> # data_policy_benthicpqt <chr>, data_policy_habitatcomplexity <chr>,
#> # data_policy_bleachingqc <chr>, created_on <chr>, updated_on <chr>This function returns information on your projects, including project countries, the number of sites, tags, data policies, and more.
To filter for specific projects, you can use the filter
function from dplyr:
library(dplyr)
indonesia_projects <- my_projects %>%
filter(countries == "Indonesia")
indonesia_projects
#> # A tibble: 5 × 15
#> id name countries num_sites tags notes status data_policy_beltfish data_policy_benthiclit
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 02e6… TWP … Indonesia 14 "WCS… "" Open Private Private
#> 2 3a9e… Aceh… Indonesia 18 "WCS… "" Open Private Private
#> 3 507d… Kari… Indonesia 43 "WCS… "" Open Private Private
#> 4 5f13… Copy… Indonesia 43 "WCS… "" Open Public Summary Public Summary
#> 5 9de8… XPDC… Indonesia 37 "" "XPD… Open Private Private
#> # ℹ 6 more variables: data_policy_benthicpit <chr>, data_policy_benthicpqt <chr>,
#> # data_policy_habitatcomplexity <chr>, data_policy_bleachingqc <chr>, created_on <chr>,
#> # updated_on <chr>Alternatively, you can search your projects using
mermaid_search_my_projects(), narrowing projects down by
name, countries, or tags:
mermaid_search_my_projects(countries = "Indonesia")
#> # A tibble: 7 × 15
#> id name countries num_sites tags notes status data_policy_beltfish data_policy_benthiclit
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 02e6… TWP … Indonesia 14 "WCS… "" Open Private Private
#> 2 2c0c… Shar… Canada, … 27 "" "dhf… Open Public Summary Public
#> 3 3a9e… Aceh… Indonesia 18 "WCS… "" Open Private Private
#> 4 507d… Kari… Indonesia 43 "WCS… "" Open Private Private
#> 5 5f13… Copy… Indonesia 43 "WCS… "" Open Public Summary Public Summary
#> 6 9de8… XPDC… Indonesia 37 "" "XPD… Open Private Private
#> 7 bacd… Beli… Belize, … 32 "WCS… "" Open Public Summary Public Summary
#> # ℹ 6 more variables: data_policy_benthicpit <chr>, data_policy_benthicpqt <chr>,
#> # data_policy_habitatcomplexity <chr>, data_policy_bleachingqc <chr>, created_on <chr>,
#> # updated_on <chr>Then, you can start to access data about your projects, like project
sites via mermaid_get_project_sites():
indonesia_projects %>%
mermaid_get_project_sites()
#> # A tibble: 155 × 12
#> project id name notes latitude longitude country reef_type reef_zone exposure created_on
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr> <chr>
#> 1 Karimun… a763… Gent… "" -5.86 111. Indone… fringing back reef shelter… 2019-03-2…
#> 2 Copy of… 2458… Gent… "" -5.86 111. Indone… fringing back reef shelter… 2022-11-1…
#> 3 Aceh Ja… 5436… Wisa… "" 5.04 95.4 Indone… fringing fore reef shelter… 2020-02-2…
#> 4 Aceh Ja… b7d5… Reha… "" 4.84 95.4 Indone… fringing fore reef shelter… 2020-02-2…
#> 5 Karimun… 0368… Meny… "" -5.80 110. Indone… fringing fore reef shelter… 2019-05-0…
#> 6 Copy of… 4f5f… Meny… "" -5.80 110. Indone… fringing fore reef shelter… 2022-11-1…
#> 7 Aceh Ja… 38f7… Pula… "" 5.08 95.3 Indone… fringing back reef semi-ex… 2020-02-2…
#> 8 Karimun… 21ae… Batu… "" -5.81 110. Indone… fringing back reef semi-ex… 2019-04-0…
#> 9 Karimun… 371b… Tanj… "" -5.83 110. Indone… fringing back reef semi-ex… 2019-04-0…
#> 10 Karimun… 43d3… Lego… "" -5.87 110. Indone… fringing back reef semi-ex… 2019-03-2…
#> # ℹ 145 more rows
#> # ℹ 1 more variable: updated_on <chr>Or the managements for your projects via
mermaid_get_project_managements():
indonesia_projects %>%
mermaid_get_project_managements()
#> # A tibble: 30 × 18
#> project id name name_secondary est_year size parties compliance open_access no_take
#> <chr> <chr> <chr> <chr> <int> <dbl> <chr> <chr> <lgl> <lgl>
#> 1 TWP Gili Su… 0975… Zona… "Core Zone" 2013 NA govern… full FALSE TRUE
#> 2 Aceh Jaya C… cc92… Core… "" 2019 NA commun… full FALSE TRUE
#> 3 Aceh Jaya C… 1498… Tour… "" 2019 NA commun… low FALSE TRUE
#> 4 Aceh Jaya C… 646c… Fish… "" 2019 NA commun… low FALSE FALSE
#> 5 Aceh Jaya C… a579… Aqua… "" 2019 NA commun… low FALSE FALSE
#> 6 Aceh Jaya C… dce8… Reha… "" 2019 NA commun… low FALSE TRUE
#> 7 Karimunjawa… 8b90… Fish… "" 2005 0 commun… low FALSE FALSE
#> 8 Karimunjawa… a7e2… Tour… "" 2005 NA commun… low FALSE TRUE
#> 9 Karimunjawa… bd73… Reha… "" 2005 NA commun… low FALSE TRUE
#> 10 Copy of Kar… 510a… Fish… "" 2005 0 <NA> low FALSE FALSE
#> # ℹ 20 more rows
#> # ℹ 8 more variables: access_restriction <lgl>, periodic_closure <lgl>, size_limits <lgl>,
#> # gear_restriction <lgl>, species_restriction <lgl>, notes <chr>, created_on <chr>,
#> # updated_on <chr>You can also access data on your projects’ Fish Belt, Benthic LIT, Benthic PIT, Bleaching, and Habitat Complexity methods. The details are in the following sections.
To access Fish Belt data for a project, use
mermaid_get_project_data() with
method = "fishbelt".
You can access individual observations (i.e., a record of each
observation) by setting data = "observations":
xpdc <- my_projects %>%
filter(name == "XPDC Kei Kecil 2018")
xpdc %>%
mermaid_get_project_data(method = "fishbelt", data = "observations")
#> # A tibble: 3,069 × 52
#> project tags country site latitude longitude reef_type reef_zone reef_exposure reef_slope
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 2 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 3 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 4 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 5 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 6 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 7 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 8 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 9 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 10 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> # ℹ 3,059 more rows
#> # ℹ 42 more variables: tide <chr>, current <chr>, visibility <chr>, relative_depth <chr>,
#> # management <chr>, management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, sample_time <time>, depth <dbl>,
#> # transect_length <dbl>, transect_width <chr>, assigned_transect_width_m <dbl>,
#> # size_bin <dbl>, observers <chr>, transect_number <dbl>, …You can access sample units data, which are observations aggregated to the sample units level. Fish belt sample units contain total biomass in kg/ha per sample unit, by trophic group and by fish family:
xpdc %>%
mermaid_get_project_data("fishbelt", "sampleunits")
#> # A tibble: 246 × 64
#> project tags country site latitude longitude reef_type reef_zone reef_exposure reef_slope
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 2 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 3 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 4 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 5 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 6 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 7 XPDC Kei… NA Indone… KE03 -5.61 132. fringing crest exposed <NA>
#> 8 XPDC Kei… NA Indone… KE03 -5.61 132. fringing crest exposed <NA>
#> 9 XPDC Kei… NA Indone… KE03 -5.61 132. fringing crest exposed <NA>
#> 10 XPDC Kei… NA Indone… KE03 -5.61 132. fringing crest exposed <NA>
#> # ℹ 236 more rows
#> # ℹ 54 more variables: tide <chr>, current <chr>, visibility <chr>, relative_depth <chr>,
#> # management <chr>, management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, sample_time <chr>, depth <dbl>,
#> # transect_number <dbl>, label <lgl>, size_bin <chr>, transect_length <dbl>,
#> # transect_width <chr>, biomass_kgha <dbl>, …And finally, sample events data, which are aggregated further, to the sample event level. Fish belt sample events contain mean total biomass in kg/ha per sample event, by trophic group and by fish family, as well as standard deviations:
xpdc_sample_events <- xpdc %>%
mermaid_get_project_data("fishbelt", "sampleevents")
xpdc_sample_events
#> # A tibble: 46 × 79
#> project tags country site latitude longitude reef_type reef_zone reef_exposure tide
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 XPDC Kei Keci… NA Indone… KE02 -5.44 133. fringing crest exposed risi…
#> 2 XPDC Kei Keci… NA Indone… KE03 -5.61 132. fringing crest exposed fall…
#> 3 XPDC Kei Keci… NA Indone… KE04 -5.58 132. fringing crest exposed risi…
#> 4 XPDC Kei Keci… NA Indone… KE05 -5.47 133. fringing crest exposed risi…
#> 5 XPDC Kei Keci… NA Indone… KE06 -5.52 132. fringing crest exposed fall…
#> 6 XPDC Kei Keci… NA Indone… KE07 -5.57 133. fringing crest exposed fall…
#> 7 XPDC Kei Keci… NA Indone… KE08 -5.55 133. fringing crest exposed fall…
#> 8 XPDC Kei Keci… NA Indone… KE09 -5.60 133. fringing fore reef semi-exposed fall…
#> 9 XPDC Kei Keci… NA Indone… KE10 -5.57 133. fringing crest exposed risi…
#> 10 XPDC Kei Keci… NA Indone… KE11 -5.59 133. fringing crest exposed risi…
#> # ℹ 36 more rows
#> # ℹ 69 more variables: current <chr>, visibility <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <lgl>, management_size <lgl>,
#> # management_parties <lgl>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, depth_avg <dbl>, depth_sd <dbl>, biomass_kgha_avg <dbl>,
#> # biomass_kgha_sd <dbl>, biomass_kgha_trophic_group_avg_omnivore <dbl>,
#> # biomass_kgha_trophic_group_avg_piscivore <dbl>, …To access Benthic LIT data, use
mermaid_get_project_data() with
method = "benthiclit".
mozambique <- my_projects %>%
filter(name == "WCS Mozambique Coral Reef Monitoring")
mozambique %>%
mermaid_get_project_data(method = "benthiclit", data = "observations")
#> # A tibble: 1,569 × 41
#> project tags country site latitude longitude reef_type reef_zone reef_exposure reef_slope
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <lgl>
#> 1 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 2 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 3 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 4 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 5 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 6 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 7 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 8 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 9 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 10 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> # ℹ 1,559 more rows
#> # ℹ 31 more variables: tide <chr>, current <lgl>, visibility <lgl>, relative_depth <lgl>,
#> # management <chr>, management_secondary <lgl>, management_est_year <dbl>,
#> # management_size <lgl>, management_parties <chr>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, sample_time <time>, depth <dbl>,
#> # transect_number <dbl>, transect_length <dbl>, label <lgl>, observers <chr>,
#> # benthic_category <chr>, benthic_attribute <chr>, …You can access sample units and sample events the same way.
For Benthic LIT, sample units contain percent cover per sample unit, by benthic category. Sample events contain mean percent cover per sample event, by benthic category, and standard deviations for these values:
mozambique %>%
mermaid_get_project_data(method = "benthiclit", data = "sampleunits")
#> # A tibble: 63 × 50
#> project tags country site latitude longitude reef_type reef_zone reef_exposure reef_slope
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <lgl>
#> 1 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 2 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 3 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 4 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 5 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 6 WCS Moza… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered NA
#> 7 WCS Moza… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef sheltered NA
#> 8 WCS Moza… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef sheltered NA
#> 9 WCS Moza… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef sheltered NA
#> 10 WCS Moza… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef sheltered NA
#> # ℹ 53 more rows
#> # ℹ 40 more variables: tide <chr>, current <lgl>, visibility <lgl>, relative_depth <lgl>,
#> # management <chr>, management_secondary <lgl>, management_est_year <dbl>,
#> # management_size <lgl>, management_parties <chr>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, sample_time <time>, depth <dbl>,
#> # transect_number <dbl>, transect_length <dbl>, label <lgl>, observers <chr>,
#> # total_length <dbl>, percent_cover_benthic_category_sand <dbl>, …To access Benthic LIT data, change method to
“benthicpit”:
xpdc %>%
mermaid_get_project_data(method = "benthicpit", data = "observations")
#> # A tibble: 11,100 × 42
#> project tags country site latitude longitude reef_type reef_zone reef_exposure reef_slope
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 2 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 3 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 4 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 5 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 6 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 7 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 8 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 9 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 10 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> # ℹ 11,090 more rows
#> # ℹ 32 more variables: tide <chr>, current <chr>, visibility <chr>, relative_depth <chr>,
#> # management <chr>, management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, sample_time <time>, depth <dbl>,
#> # transect_number <dbl>, transect_length <dbl>, interval_start <dbl>, interval_size <dbl>,
#> # label <lgl>, observers <chr>, …You can access sample units and sample events the same way, and the data format is the same as Benthic LIT.
You can return both sample units and sample events by setting the
data argument. This will return a list of two data frames:
one containing sample units, and the other sample events.
xpdc_sample_units_events <- xpdc %>%
mermaid_get_project_data(method = "benthicpit", data = c("sampleunits", "sampleevents"))
names(xpdc_sample_units_events)
#> [1] "sampleunits" "sampleevents"
xpdc_sample_units_events[["sampleunits"]]
#> # A tibble: 111 × 51
#> project tags country site latitude longitude reef_type reef_zone reef_exposure reef_slope
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 2 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 3 XPDC Kei… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 4 XPDC Kei… NA Indone… KE03 -5.61 132. fringing crest exposed <NA>
#> 5 XPDC Kei… NA Indone… KE03 -5.61 132. fringing crest exposed <NA>
#> 6 XPDC Kei… NA Indone… KE03 -5.61 132. fringing crest exposed <NA>
#> 7 XPDC Kei… NA Indone… KE04 -5.58 132. fringing crest exposed <NA>
#> 8 XPDC Kei… NA Indone… KE04 -5.58 132. fringing crest exposed <NA>
#> 9 XPDC Kei… NA Indone… KE04 -5.58 132. fringing crest exposed <NA>
#> 10 XPDC Kei… NA Indone… KE05 -5.47 133. fringing crest exposed <NA>
#> # ℹ 101 more rows
#> # ℹ 41 more variables: tide <chr>, current <chr>, visibility <chr>, relative_depth <chr>,
#> # management <chr>, management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, sample_time <time>, depth <dbl>,
#> # transect_number <dbl>, transect_length <dbl>, label <lgl>, interval_start <dbl>,
#> # interval_size <dbl>, observers <chr>, …To access Bleaching data, set method to “bleaching”.
There are two types of observations data for the Bleaching method:
Colonies Bleached and Percent Cover. These are both returned when
pulling observations data, in a list:
bleaching_obs <- mozambique %>%
mermaid_get_project_data("bleaching", "observations")
names(bleaching_obs)
#> [1] "colonies_bleached" "percent_cover"
bleaching_obs[["colonies_bleached"]]
#> # A tibble: 1,814 × 43
#> project tags country site latitude longitude reef_type reef_zone reef_exposure tide
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <lgl>
#> 1 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> 2 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> 3 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> 4 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> 5 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> 6 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> 7 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> 8 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> 9 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> 10 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> # ℹ 1,804 more rows
#> # ℹ 33 more variables: current <lgl>, visibility <lgl>, relative_depth <lgl>, management <chr>,
#> # management_secondary <lgl>, management_est_year <dbl>, management_size <lgl>,
#> # management_parties <chr>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, sample_time <time>, depth <dbl>, quadrat_size <dbl>, label <chr>,
#> # observers <chr>, benthic_attribute <chr>, growth_form <chr>, count_normal <dbl>,
#> # count_pale <dbl>, …The sample units and sample events data contain summaries of both Colonies Bleached and Percent Cover:
mozambique %>%
mermaid_get_project_data("bleaching", "sampleevents")
#> # A tibble: 62 × 49
#> project tags country site latitude longitude reef_type reef_zone reef_exposure tide
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <lgl>
#> 1 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed NA
#> 2 WCS Mozambiqu… WCS … Mozamb… Baby… -11.0 40.7 fringing fore reef exposed NA
#> 3 WCS Mozambiqu… WCS … Mozamb… Balu… -22.0 35.5 patch fore reef exposed NA
#> 4 WCS Mozambiqu… WCS … Mozamb… Dos … -12.1 40.6 lagoon back reef sheltered NA
#> 5 WCS Mozambiqu… WCS … Mozamb… Fing… -12.9 40.6 fringing fore reef exposed NA
#> 6 WCS Mozambiqu… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered NA
#> 7 WCS Mozambiqu… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered NA
#> 8 WCS Mozambiqu… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered NA
#> 9 WCS Mozambiqu… WCS … Mozamb… Libe… -14.5 40.7 fringing back reef sheltered NA
#> 10 WCS Mozambiqu… WCS … Mozamb… Ligh… -12.3 40.6 fringing fore reef exposed NA
#> # ℹ 52 more rows
#> # ℹ 39 more variables: current <lgl>, visibility <lgl>, management <chr>,
#> # management_secondary <lgl>, management_est_year <dbl>, management_size <lgl>,
#> # management_parties <chr>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, depth_avg <dbl>, depth_sd <dbl>, quadrat_size_avg <dbl>,
#> # count_total_avg <dbl>, count_total_sd <dbl>, count_genera_avg <dbl>, count_genera_sd <dbl>,
#> # percent_normal_avg <dbl>, percent_normal_sd <dbl>, percent_pale_avg <dbl>, …Finally, to access Habitat Complexity data, set method
to “habitatcomplexity”. As with all other methods, you can access
observations, sample units, and sample events:
xpdc %>%
mermaid_get_project_data("habitatcomplexity", "sampleevents")
#> # A tibble: 2 × 33
#> project tags country site latitude longitude reef_type reef_zone reef_exposure tide current
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr> <chr>
#> 1 XPDC K… NA Indone… KE22 -5.85 133. fringing fore reef exposed risi… low/no…
#> 2 XPDC K… NA Indone… KE24 -5.93 133. fringing fore reef exposed risi… low/no…
#> # ℹ 22 more variables: visibility <chr>, management <chr>, management_secondary <chr>,
#> # management_est_year <lgl>, management_size <lgl>, management_parties <lgl>,
#> # management_compliance <lgl>, management_rules <chr>, sample_date <date>, depth_avg <dbl>,
#> # depth_sd <dbl>, score_avg_avg <dbl>, score_avg_sd <dbl>,
#> # data_policy_habitatcomplexity <chr>, project_notes <chr>, site_notes <lgl>,
#> # management_notes <lgl>, id <chr>, sample_unit_count <dbl>, project_admins <chr>, …To pull data for both fish belt and benthic PIT methods, you can set
method to include both.
xpdc_sample_events <- xpdc %>%
mermaid_get_project_data(method = c("fishbelt", "benthicpit"), data = "sampleevents")The result is a list of data frames, containing sample events for both fish belt and benthic PIT methods:
names(xpdc_sample_events)
#> [1] "fishbelt" "benthicpit"
xpdc_sample_events[["benthicpit"]]
#> # A tibble: 38 × 55
#> project tags country site latitude longitude reef_type reef_zone reef_exposure tide
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 XPDC Kei Keci… NA Indone… KE02 -5.44 133. fringing crest exposed <NA>
#> 2 XPDC Kei Keci… NA Indone… KE03 -5.61 132. fringing crest exposed fall…
#> 3 XPDC Kei Keci… NA Indone… KE04 -5.58 132. fringing crest exposed risi…
#> 4 XPDC Kei Keci… NA Indone… KE05 -5.47 133. fringing crest exposed <NA>
#> 5 XPDC Kei Keci… NA Indone… KE06 -5.52 132. fringing crest exposed risi…
#> 6 XPDC Kei Keci… NA Indone… KE07 -5.57 133. fringing crest exposed <NA>
#> 7 XPDC Kei Keci… NA Indone… KE08 -5.55 133. fringing crest exposed fall…
#> 8 XPDC Kei Keci… NA Indone… KE09 -5.60 133. fringing fore reef semi-exposed fall…
#> 9 XPDC Kei Keci… NA Indone… KE10 -5.57 133. fringing crest exposed risi…
#> 10 XPDC Kei Keci… NA Indone… KE11 -5.59 133. fringing crest exposed risi…
#> # ℹ 28 more rows
#> # ℹ 45 more variables: current <chr>, visibility <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <lgl>, management_size <lgl>,
#> # management_parties <lgl>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, depth_avg <dbl>, depth_sd <dbl>,
#> # percent_cover_benthic_category_avg_sand <dbl>,
#> # percent_cover_benthic_category_avg_trash <dbl>, …Alternatively, you can set method to “all” to pull for
all methods! Similarly, you can set data to “all” to pull
all types of data:
all_project_data <- xpdc %>%
mermaid_get_project_data(method = "all", data = "all", limit = 1)
names(all_project_data)
#> [1] "fishbelt" "benthiclit" "benthicpit" "benthicpqt"
#> [5] "bleaching" "habitatcomplexity"
names(all_project_data[["benthicpit"]])
#> [1] "observations" "sampleunits" "sampleevents"Pulling data for multiple projects is the exact same, except there
will be an additional “project” column at the beginning to distinguish
which projects the data comes from. Recall that my_projects
contains six projects:
my_projects
#> # A tibble: 19 × 15
#> id name countries num_sites tags notes status data_policy_beltfish
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 02e6915c-1c64-4d2c-bac0-32… TWP … Indonesia 14 "WCS… "" Open Private
#> 2 170e7182-700a-4814-8f1e-45… 2018… Fiji 10 "WCS… "Thi… Open Private
#> 3 173c2353-3ee3-49d1-b08a-a6… Copy… Fiji 8 "WCS… "Nam… Open Public Summary
#> 4 1fbdb9ea-9adf-4038-bbe2-52… a2 Canada, … 9 "WWF… "Nam… Open Private
#> 5 2c0c9857-b11c-4b82-b7ef-e9… Shar… Canada, … 27 "" "dhf… Open Public Summary
#> 6 2d6cee25-c0ff-4f6f-a8cd-66… WCS … Mozambiq… 74 "WCS… "Dat… Open Private
#> 7 3a9ecb7c-f908-4262-8769-1b… Aceh… Indonesia 18 "WCS… "" Open Private
#> 8 4080679f-1145-4d13-8afb-c2… Mada… Madagasc… 74 "WCS… "MAC… Open Private
#> 9 4d23d2a1-774f-4ccf-b567-69… Mada… Madagasc… 16 "WCS… "Mon… Open Public Summary
#> 10 507d1af9-edbd-417e-a65c-35… Kari… Indonesia 43 "WCS… "" Open Private
#> 11 5679ef3d-bafc-453d-9e1a-a4… Mada… Madagasc… 33 "WCS… "" Open Public Summary
#> 12 5f13e6dc-40cc-4ef9-9c16-ae… Copy… Indonesia 43 "WCS… "" Open Public Summary
#> 13 75ef7a5a-c770-4ca6-b9f8-83… Kubu… Fiji 78 "WCS… "" Open Private
#> 14 7a6bfd69-6635-4281-937c-2b… Copy… Belize 31 "WCS… "" Open Public Summary
#> 15 9de82789-c38e-462e-a1a8-e0… XPDC… Indonesia 37 "" "XPD… Open Private
#> 16 a1b7ff1f-81cd-4efc-978b-cf… Grea… Fiji 76 "Uni… "" Open Private
#> 17 bacd3529-e0f4-40f4-a089-99… Beli… Belize, … 32 "WCS… "" Open Public Summary
#> 18 d065cba4-ed09-47fd-89fb-22… 2019… Fiji 31 "WCS… "Ble… Open Private
#> 19 e1efb1e0-0af8-495a-9c69-fd… 2016… Fiji 8 "WCS… "Nam… Open Private
#> # ℹ 7 more variables: data_policy_benthiclit <chr>, data_policy_benthicpit <chr>,
#> # data_policy_benthicpqt <chr>, data_policy_habitatcomplexity <chr>,
#> # data_policy_bleachingqc <chr>, created_on <chr>, updated_on <chr>
my_projects %>%
mermaid_get_project_data("fishbelt", "sampleevents", limit = 1)
#> # A tibble: 13 × 157
#> project tags country site latitude longitude reef_type reef_zone reef_exposure tide
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 TWP Gili Sula… WCS … Indone… Peda… -8.28 117. fringing crest exposed high
#> 2 2018_Vatu-i-R… WCS … Fiji VIR1 -17.3 178. barrier fore reef exposed fall…
#> 3 Sharla test <NA> Indone… 1201 -2.02 134. fringing fore reef exposed high
#> 4 WCS Mozambiqu… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed <NA>
#> 5 Aceh Jaya Coa… Vibr… Indone… Abah… 4.99 95.4 fringing fore reef exposed high
#> 6 Madagascar WC… WCS … Madaga… Kisi… -13.6 48.1 fringing fore reef exposed <NA>
#> 7 Karimunjawa N… WCS … Indone… Batu… -5.81 110. fringing back reef semi-exposed low
#> 8 Madagascar Ba… WCS … Madaga… Anta… -16.4 49.8 fringing fore reef semi-exposed <NA>
#> 9 Kubulau 2009-… WCS … Fiji C13 -17.0 179. barrier fore reef semi-exposed fall…
#> 10 XPDC Kei Keci… <NA> Indone… KE02 -5.44 133. fringing crest exposed risi…
#> 11 Great Sea Ree… Fiji… Fiji BA02 -17.4 178. atoll back reef very shelter… fall…
#> 12 Belize Glover… WCS … Belize CZFR1 16.7 -87.8 atoll fore reef exposed <NA>
#> 13 2016_Namena M… WCS … Fiji C3 -17.1 179. barrier fore reef exposed <NA>
#> # ℹ 147 more variables: current <chr>, visibility <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <dbl>, management_size <dbl>,
#> # management_parties <chr>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, depth_avg <dbl>, depth_sd <dbl>, biomass_kgha_avg <dbl>,
#> # biomass_kgha_sd <dbl>, biomass_kgha_trophic_group_avg_omnivore <dbl>,
#> # biomass_kgha_trophic_group_avg_piscivore <dbl>,
#> # biomass_kgha_trophic_group_avg_planktivore <dbl>, …Note the limit argument here, which just limits the data
pulled to one record (per project, method, and data combination). This
is useful if you want to get a preview of what your data will look like
without having to pull it all in.
Prior to mermaidr 0.7.0, covariates were automatically
included in all mermaid_get_project_data() function calls.
Now, to access covariates, include covariates = TRUE in the
function call:
my_projects %>%
head(1) %>%
mermaid_get_project_data("fishbelt", "sampleevents", limit = 1, covariates = TRUE)
#> # A tibble: 1 × 87
#> site_id project tags country site latitude longitude reef_type reef_zone reef_exposure tide
#> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 369a0b… TWP Gi… WCS … Indone… Peda… -8.28 117. fringing crest exposed high
#> # ℹ 76 more variables: current <chr>, visibility <chr>, aca_geomorphic <chr>,
#> # aca_benthic <chr>, andrello_grav_nc <dbl>, andrello_sediment <dbl>,
#> # andrello_nutrient <dbl>, andrello_pop_count <dbl>, andrello_num_ports <dbl>,
#> # andrello_reef_value <dbl>, andrello_cumul_score <dbl>, beyer_score <dbl>,
#> # beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>, beyer_scoreth <dbl>,
#> # beyer_scoretr <dbl>, management <chr>, management_secondary <chr>,
#> # management_est_year <dbl>, …You can also access covariates at the site level, using
mermaid_get_project_sites() with
covariates = TRUE:
my_projects %>%
mermaid_get_project_sites(covariates = TRUE)
#> # A tibble: 662 × 27
#> project id name notes latitude longitude country reef_type reef_zone exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 Great Sea Reef 2019 0235… BA09 "" -17.4 178. Fiji atoll back reef very sh…
#> 2 Great Sea Reef 2019 0879… BA16 "" -17.2 178. Fiji atoll back reef very sh…
#> 3 Great Sea Reef 2019 1925… BA15 "" -17.2 178. Fiji atoll back reef very sh…
#> 4 Great Sea Reef 2019 19e6… YA02 "" -17.0 177. Fiji atoll back reef very sh…
#> 5 Great Sea Reef 2019 20ae… BA11 "" -17.3 178. Fiji atoll back reef very sh…
#> 6 Great Sea Reef 2019 2af4… BA12 "" -17.3 178. Fiji atoll back reef very sh…
#> 7 Great Sea Reef 2019 2f08… BA10 "" -17.3 178. Fiji atoll back reef very sh…
#> 8 Great Sea Reef 2019 364f… YA08 "" -17.0 177. Fiji atoll back reef very sh…
#> 9 Great Sea Reef 2019 3888… YA03 "" -16.9 177. Fiji atoll back reef very sh…
#> 10 Great Sea Reef 2019 3ceb… LW07 "Adj… -17.6 177. Fiji atoll back reef very sh…
#> # ℹ 652 more rows
#> # ℹ 17 more variables: aca_geomorphic <chr>, aca_benthic <chr>, andrello_grav_nc <dbl>,
#> # andrello_sediment <dbl>, andrello_nutrient <dbl>, andrello_pop_count <dbl>,
#> # andrello_num_ports <dbl>, andrello_reef_value <dbl>, andrello_cumul_score <dbl>,
#> # beyer_score <dbl>, beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>,
#> # beyer_scoreth <dbl>, beyer_scoretr <dbl>, created_on <chr>, updated_on <chr>